MétaCan
Menu
Back to cohort

Theoretical Prediction of a Time-Reversal Broken Chiral Superconducting Phase Driven by Electronic Correlations in a Single<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mi>TiSe</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math>Layer

2014· article· lv· W1498157129 on OpenAlexaff
R. Ganesh, G. Baskaran, Jeroen van den Brink, Dmitry V. Efremov

Bibliographic record

VenuePhysical Review Letters · 2014
Typearticle
Languagelv
FieldMaterials Science
TopicIron-based superconductors research
Canadian institutionsPerimeter Institute
FundersDepartment of Atomic Energy, Government of India
KeywordsSuperconductivityPhase (matter)PhysicsComputer scienceCondensed matter physicsQuantum mechanics

Abstract

fetched live from OpenAlex

Bulk TiSe2 is an intrinsically layered transition metal dichalcogenide hosting both superconducting and charge-density-wave ordering. Motivated by the recent progress in preparing two-dimensional transition metal dichalcogenides, we study these frustrated orderings in a single trilayer of TiSe2. Using a renormalization group approach, we find that electronic correlations can give rise to charge-density-wave order and two kinds of superconductivity. One possible superconducting state corresponds to unconventional s(+-) pairing. The other is particularly exciting as it is chiral, breaking time-reversal symmetry. Its stability depends on the precise strength and screening of the electron-electron interactions in two-dimensional TiSe2.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.267
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations49
Published2014
Admission routes1
Has abstractyes

Explore more

Same venuePhysical Review LettersSame topicIron-based superconductors researchFrench-language works237,207